Workiva Redesigns Finance Workflows Around AI, Not Productivity Tricks
Enterprise software maker Workiva is building AI capabilities for finance and compliance teams by starting with business outcomes rather than individual efficiency gains. The company's approach emphasizes trusted data and employee adoption as core to AI-native workflow design.

Constructing workflows that are truly AI-native demands beginning with the specific business result an organization seeks to accomplish. The effort entails fundamentally reconsidering the interplay between workforce, operations and information across the full scope of a given undertaking.
Workiva Inc., which develops enterprise software, is putting this philosophy into practice as it builds tools targeting finance and compliance professionals. Moving past gains in individual worker output to achieve concrete business improvements represents the real measure of success, according to Kim Huffman, Workiva's chief information officer.
I think AI is a fundamental technology that's going to reshape the landscape of technology portfolios in every organization. When you think of it as a bolt-on capability, you're probably going to get bolt-on outcomes.
Kim Huffman, chief information officer of Workiva
Huffman shared these perspectives during a conversation with theCUBE Research's Krista Case and co-host Alison Kosik at Workiva's Amplify event, which aired as an exclusive broadcast on theCUBE, SiliconANGLE Media's livestreaming platform. The discussion covered workflow transformation, data reliability and how organizations can get employees to embrace new systems.
Building AI-native workflows on trusted data
Creating workflows powered by AI requires gathering staff from multiple departments to collectively establish a common objective. Organizations can then pinpoint areas where artificial intelligence might handle portions of the work while maintaining space for human review and sign-off on AI decisions. Preparing the workforce for this transition is crucial, Huffman emphasized.
AI has amplified … the importance of data quality, data trust and data governance. Historically, people have looked at some of the governance functions around data as potentially slowing down the speed of how organizations want to move. But in the era of AI, I actually view governance as the ability to move faster. If you can build strong governance, you have a greater degree of trust so that you're able to trust the outputs.
Kim Huffman
The company unveiled Agent Studio at the event, a tool that allows users to construct and tailor agents without needing to code. Providing staff with these capabilities can surface possibilities that technical teams might have overlooked, Huffman noted.
https://www.youtube.com/embed/ZtOfr3KRLwE?feature=oembed
I think the biggest 'aha' moment was how quickly the teams that were introduced to Agent Studio were able to understand it and were able to build something that was really valuable in a very short period of time. In days, they were able to get something that worked for them for their specific use case, and they were able to see immediate results.
Kim Huffman


